Best metric to evaluate model probabilities

i'm trying to create ML model for binary classification problem with balanced dataset and i care mostly about probabilities. I was trying to search web and i find only advices to use AUC or logloss scores. There is no advices to use Brier score as evaluation metric. Can i use brier score as evaluation metric or there is some pitfalls within it? As i can understand if i will use logloss score as evaluation metric the winner one model will be the one who has probabilities closer to 0-10% and 90-100%.